Category Archives: Trends

A Tack Board of Tags (HOTW July 19, 2015)

There have been some fantastic conversations on Twitter this week, on a huge diversity of topics and organized around some intriguing hashtags. I was personally involved with the Summit for the Mayo Clinic Center for Social Media (#MCCSM) and the local systematic review training course (UMTHLSysRev). It was a series of happy coincidences that led me to the events Astrobiology Science Conference 2015 (#AbSciCon); Inspirefest 2015, the future of science, technology, engineering, and mathematics with new perspectives on innovation, leadership and success (#inspirefest2015); and International Association for Suicide Prevention (#IASP2015). I was surprised to find two very relevant Twitter chats that were new to me: hereditary cancer chat (#hcchat) and the Internet of Things chat (#IoTchat). Last but far from least, the nursing-inspired #WhyWeDoResearch tag is a very motiving and inspiring meme to explore. I’ll put just a few examples of each below, hoping to intrigue you enough to go look at these yourself.



Mayo Clinic Center for Social Media | #MCCSM (#mccsm archive)



Systematic Reviews Workshop: Opportunities for Librarians |
#umthlsysrev (#umthlsysrev archive)



Astrobiology Science Conference 2015 | #AbSciCon



Inspirefest | #inspirefest2015



28th World Congress of the International Association for Suicide Prevention, Montreal, 2015 | #IASP2015 (#IASP2015 archive)



Hereditary Cancer Chat #HCchat
(#HCchat archive)



#IoTChat: Internet of Things Twittersphere Chats Evolve | #IoTchat



Why We Do Research Campaign (Weebly sites blocked in UM hospitals) [Campaign video 1; campaign video 2] | #WhyWeDoResearch (#WhyWeDoResearch archive)

What’s New, What’s Hot: My Favorite Posters from #MLAnet15

Part 3 of a series of blogposts I wrote for the recent Annual Meeting of the Medical Library Association.


I had a particular slant, where I was looking for new technology posters, emerging and emergent innovations, but then I was so delighted with the richness of systematic review research being presented, that there is a lot of that, too. The chosen few ran from A to Z, with apps, bioinformatics, data visualization, games, Google Glass in surgery, new tech to save money with ILL operations, social media, Youtube, zombies, and even PEOPLE. What is it with medical librarians and zombies? Hunh. Surely there are other gory engaging popular medical monsters? Anyway, here are some of my favorite posters from MLA’s Annual Meeting. There were so many more which I loved and tweeted, but I just can’t share them all here today. I’ll try to put them in a Storify when I get back home. Meanwhile, look these up online or in the app for more details. By the way, they started to get the audio up, so you can use the app to listen to many of the presenters talk about their poster.

Poster 14:

Poster 28:

Poster 30:

Poster 38:

Poster 40 (and that should read “Twitter”, not “Titter”):

Poster 43:

Poster 54:

Poster 65:

Poster 83:

Poster 100:

Poster 121:

Poster 125:

Poster 130:

Poster 157:

Poster 202:

Poster 224:

Poster 225:

Poster 228:

Poster 238:

Poster 243:

Tech Trends VIII (#mlanet15)

Part 2 of a series of blogposts I wrote for the recent Annual Meeting of the Medical Library Association.


#MLATTT #MLANET15

The event so fondly known as MLATTT is a gathering of a panel of medical librarians who describe new and emerging technologies in what has become, by a kind of traditional, highly entertaining and engaging ways. For many, it is a not-to-be-missed highlight of the annual Medical Library Association meeting. This year was no different, and if anything topped previous years for sheer blistering hilarity. When the video becomes available, this is a must watch. I plan to watch it again, and I was there!

#MLATTT #MLANET15

Eric Schnell gave a talk that had the older members of the audience guffawing with laughter as he extolled the pleasures of emerging technologies from the perspective of the 1980s and 1990s. There were some younger folk asking, “Mosiac? Atari?” It was extremely well scripted and supported with links and images, and delivered completely deadpan.

#MLATTT #MLANET15

The quantified self section presented by Jon Goodall was great fun for me, and I particularly enjoyed how he engaged the audience in reviews of some of the highlighted technologies. It was interesting to see who had used various tools, and whether they worked for them or not.

#MLATTT #MLANET15

Kimberley Barker was incredibly dynamic, personable, and knowledgeable, as she sprinted through a rapidfire, high energy delivery of examples of tools, technologies, and trends relative to what’s happening with the Internet of Things.

#MLATTT #MLANET15

Jason Bengtson gave a candid, rollicking walk-through of some of his thoughts and experiences while creating the engaging information skills tutorial, Zombie Emergency. I was really impressed with how clearly he described the challenges of integrating education goals and content with gaming. Rachel Walden expressed well what I was thinking, when she commented on how impressive it was that Jason coded this, and is giving away the code for free in Github, as CC-licensed. You can find the actual quotes in the Storify, listed at the end of this post.

#MLATTT #MLANET15

J. Dale Prince might have been last, but far from least, as he wittily recounted his tales of being a new Apple Watch owner, pros, cons, and maybes. By the way, if you decide to buy a gold Apple Watch, Dale is willing to trade. ;)

Here’s the Storify, with much much more detail.

An archive of the tweets is available here, through Symplur. Almost 400 tweets in one hour?! That should tell you how much fun folk were having!

http://www.symplur.com/healthcare-hashtags/mlattt/

Molecular Biology & Genomics SIG Meeting #mlanet15

Part 1 of a series of blogposts I wrote for the recent Annual Meeting of the Medical Library Association.


MolBio & Genomics SIG #mlanet15

I’m trying to track what’s going on with emerging technologies, new tools, new-to-me tools, and so forth. I’m not an official member of the MolBioGen SIG, but I wish I was (especially since personal genomics is one of my hobbies). I learned so much at their meeting Monday morning. The best part was the Round Table, where they each talked about who they are, what they do, what’s new at their place. Now, this was exciting! They talked about many tools they seemed to all know and take for granted, and I’ll share some of those later. They also had so many exciting and creative ideas for how to engage their target audiences, types of classes that are most effective, crowdsourcing instruction from within the audience, strategic partnerships that make a difference, strategies for point-of-care genomics, and so much more.

Here are the tools that I found most interesting.

PhenoTips
PhenoTips

Reactome
Reactome

Online Bioinformatics Resource Collection
Bioinformatics MOOCs Example

Galaxy Project
Galaxy

Open Helix
OpenHelix
(Note: These folk are in the Exhibit Hall, if you haven’t seen them yet.)

BioStars
BioStars

GenePool
GenePool

Data Carpentry
Data Carpentry

Project Hydra
Hydra

Fedora
Fedora

NCBI: Gene Expression Omnibus (GEO)
GEO (Gene Expression Omnibus)

Complete Genome: Public Genome Data
Complete Genomics Public Data

NYU Data Catalog
NYU Data Catalog

Want more? Check out the Storify!

Informed Consent in a New Era

Informed Consent copy

I’m a big fan of John Wilbanks’ work in the area of open personal health data and informed consent, and have blogged about that here before. Briefly, my awareness of John’s work began with “We Consent” which has now transformed into Sage’s “Participant Centered Consent Toolkit.”

Cool Toys Pic of the day - We Consent
Sage: Participant-Centered Consent Toolkit (E-Consent)

Recently someone asked me a question about “online informed consent.” I think they were remembering my having mentioned John Wilkin’s stuff, a.k.a “portable legal consent” or “portable informed consent.” These and “online informed consent” are … related concepts, but perhaps not as closely related as some might think. Just to complicate matters, people are also using jargon like “dynamic consent” and “broad consent” to mean things related to both of these, but which are not quite the same. There are also people trying to get the phrase “informed consent” converted to “educated consent” as possibly being more meaningful. In this post, I will try to sort some of this out, but I’m no kind of expert in consent, and this is complicated, really REALLY complicated.

First, the short-short explanation. Portable informed consent (PIC) usually is part of online informed consent, but online informed consent (OIC) is rarely portable. Riiiight. OK, a step backwards.

PORTABLE CONSENT

The idea of portable informed consent is (in my mind, at least) analogous to Creative Commons licensing for your own creative works, except that it applies to your own health data. Actually, the idea of this really came from people wanting to share genomic data. You walk through an online informed consent process, agree to which version of a license you are comfortable with, and then when you share your data in a secure repository, that license or consent agreement is attached. People who want to use your data, must agree to follow those predetermined restrictions. Researchers who don’t agree, aren’t allowed to see your data, only data from other folk who agree to whatever guidelines they need for their project. Researchers who don’t follow the rules will be denied access to all of the data.

Personal Genomics

Genomics is basically mapping the genome. Personal genomics is doing this for a person in particular, rather than a species or condition or other collective group. Some people get involved in exploring personal genomics because of simple curiosity, but many are driven by long standing medical challenges without any easily identifiable solution. Some people are terrified at the idea of what they might find out. Others are concerned that the data will result in problems with jobs or insurance. Those urgently seeking help for health problems often want to share and find others who might have insights into their problem. OpenSNP and the Personal Genome Project are two examples of places where people share their genomic data. By making their data public and consenting to its use by researchers, they are hoping to support solutions not only for themselves but for others like them. Making sure that consent is LEGAL is essential for supporting future research. One great example of this is Jay Lake, who contributed his whole DNA sequencing data and that of his tumor, making possible research on new treatments that came too late for him. It’s a powerful story.

ONLINE INFORMED CONSENT

Online informed consent is a great deal simpler, in that it mostly takes the usual informed consent process (reading forms, signing forms, filing forms) and puts it all into an online web-based interface in a secure system. But, PIC gets more buzz in the popular press and media, while OIC gets more attention from within the hallways of day-to-day research communities. PIC grew out of work with personal genomics and is designed to make data sharing simpler, research more open, and problem solving more dynamic, all while still being responsive to issues of privacy and ethics. OIC is a tool designed to make the IRB management simpler for researchers.

DYNAMIC CONSENT

Dynamic consent is closer to portable consent, but grew more out of tissue and biobanking contexts, rather than data or genomics. Dynamic consent has a lot of nitpicky little options, and allows you to change your mind over time. That’s why it’s dynamic — things keep changing. Right now, dynamic consent is used primarily for what happens to parts of your body that are removed from your body while you are alive, and used for various medical purposes. Sometimes those purposes involved throwing what wasn’t used in the nearest incinerator, but sometimes there is something interesting and the doctors or researchers want to keep a sample for future use.

Biobanking

Now, remember, I’m drastically oversimplifying here. There are many more situations and options that come into play. Healthcare researchers have come to realize that we often don’t know where the next interesting possibility will come from, which is part of why biobanking is becoming more important. A biobank is sort of a library of tissues (meaning parts of human or animals or plants). Biobanks are often focused on a certain type of tissue or condition. Many biobanks collect tissues for a particular kind of cancer, or conditions like Parkinson’s, Alzheimer, autism, etc. Others may focus on a particular organ, like brains, breast tissue, lungs, or genome. In book and journal libraries, the librarians have traditionally spent a lot of time trying to select just the most important material on their special topics, but over generations, we’ve found the most desired content is as often as not the parts that were considered cheap and unimportant at the time, which are now expensive and hard to find, because no one kept them. Some of the same issues are coming up with biobanking, but complicated by the challenge of each and every sample being unique (although there might be copies of cell lines). At least with books, if one library lost theirs, another library might have a copy. Part of the idea of all these different kinds of consent is to try to maximise the number and diversity of samples that can be preserved and made accessible to future researchers.

PRESUMED CONSENT

Presumed consent also related to tissues, actually organ donation, but after you are no longer alive or aware enough to give or change your consent. Where I live, you have to register as an organ donor. If you don’t, and are in a fatal accident, no one is allowed to use your organs as transplants to save the lives of other folk who need new organs to survive. That isn’t how it works in all countries, though. In some countries they have “presumed consent,” where the assumption is that organ donation is fine with you as long as you don’t say NO beforehand. So, opt-in vs. opt-out. That’s the main difference. Sounds simple, doesn’t it? But people have incredibly strong feelings about both of these options.

BROAD CONSENT

Broad consent is probably the messiest of all of these. Just look at these article titles!

Can Broad Consent be Informed Consent?

Broad consent is informed consent

Broad consent versus dynamic consent in biobank research: Is passive participation an ethical problem?

Broad Consent Versus Dynamic Consent: Pros And Cons For Biobankers To Consider

Broad Consent in Biobanking: Reflections on Seemingly Insurmountable Dilemmas

Should donors be allowed to give broad consent to future biobank research?

You can just feel the tensions rising as you read through the list. It is obvious that this is not an area of consensus. And what can it possibly mean to consent mean when there isn’t an agreement about what consent is?

“Broad consents are not open nor are blanket consents. To give a broad consent means consenting to a framework for future research of certain types.” Steinsbekk KS, Myskja BK, Solberg B. Broad consent versus dynamic consent in biobank research: Is passive participation an ethical problem? European Journal of Human Genetics (2013) 21:897–902.

Broad consent attempts to make a best guess of what might be needed by the researcher of the future, and to try to get the individual to agree to a flexible use and reuse of tissues, samples, or data. As you can tell from the titles above, “broad consent” tends to refer to tissues rather than data, but when you get down to brass tacks, all of these could theoretically apply to a wide variety of donated content.

CLOSING THOUGHTS

The idea behind all of these myriad forms of consent is knotted into the dynamic between the rights of the individual and the needs of the community. Without research, we stagnate and die, literally, since solutions cannot be discovered for the aches and pains and problems that lead to increased mortality and reduced longevity. As a community, as a species, we don’t make progress without sharing. At the same time, the goal is to reduce harm to individuals, and forcing people to ‘consent’ against their will causes harm. I’ve known people who practically had a nervous breakdown at the idea of becoming an organ donor, the idea of part of them living on in someone else distressed them that deeply. I know others who fear what could happen to them if their genetic data fell into the “wrong hands.” I’m not one of them. I’m a registered organ donor, and I donated my genomic data to OpenSNP. But I still respect the emotional pain that would be caused by forcing consent. It’s an ethical dilemma which our society is obviously still working to solve. While looking at background material for this post I stumbled across two phrases that seemed to express some of the challenges well: “From Informed Consent to No Consent?” “Open Consent for Closed Minds.”

“I’m proposing … that we reach into our bodies and we grab the genotype, and we reach into the medical system and we grab our records, and we use it to build something together.” “I hate [the] word ‘patient.’ I don’t like being patient when … health care is broken.” John Wilbanks

Personalized Medicine, Biosensors, Mobile Medical Apps, and More

At the Quantified Self Meetup, someone was praising the Rock Health slides. Of course, I had to go explore and see what was so great. These are my favorites.

About FDA’s Guidance for Mobile Medical Apps

FDA 101: A guide to the FDA for digital health entrepreneurs by @Rock_Health: http://www.slideshare.net/RockHealth/fda-101-a-guide-to-the-fda-for-digital-health-entrepreneurs

I especially took note of slide 10, where they describe things I would think of as an app, but which do not qualify as such for FDA regulation. This is an important distinction I hadn’t previously considered. Slide 12 takes it further by describing the categories of regulation as based on risk to patients, with good clear examples. Slie 21 on “pro tips” would have really benefitted companies like 23andMe (even though that isn’t actually a mobile medical app, the pro tips still apply, and in spades).

Biosensing Wearable Tech

The Future of Biosensing Wearables by @Rock_Health http://www.slideshare.net/RockHealth/the-future-of-biosensing-wearables-by-rockhealth

This one definitely gets into topics relevant to the quantified self movement and self-tracking. Slide six emphasizes the shift from the low hanging fruit (fitness, pulse, sleep) to the long tail — more targeted solutions for specific challenges (hydration, glucose, salinity, skin conductance, posture, oxygenation, heart rhythm, respiration, eyetracking, brain activity, etc.). That’s really quite interesting, and it gives examples of companies working in each space.

Slides 19-24 get into several of the areas our own local meetup defined as challenges to success for companies working in this space and for the future success of the entire area — it has to work, easily, and dependably. Slides 27-30 extrapolate these challenges into the transition into healthcare environments.

Personalized Medicine

The Future of Personalized Health Care: Predictive Analytics by @Rock_Health http://www.slideshare.net/RockHealth/the-future-of-personalized-health-care-predictive-analytics-press Video https://www.youtube.com/watch?v=UJak41hIDWc

SLIDES

VIDEO

It’s probably safe to say that most individuals working in the quantified self / self-tracking space eventually end up struggling with the issue of how to use their data to anticipate avoidable problems. This idea can be translated into the jargon phrase of “predictive analytics.” Slide 11 does a nice job of lining this up with how traditional healthcare is practiced, which is very useful. Slide 12 places this in the context of big data resources, databases, and tools, listing several of the main players. This context is essential for making personal data relevant beyond the drawn out process of n=1 studies. Slide 14 identifies the BIG problem of how companies working in this space largely focus on hospitals and health care providers, and seem to have entirely missed the idea that patients are deeply and actively engaged in this space. And, frankly, there are more of us than them (even if our pockets aren’t as deep). I love the phrase on slide 18, “Symptom calculators are the “recommendation engines” of health care.” Most of the rest of the deck identifies challenges and opportunities, which I hope any entrepreneurial types would examine closely. Do notice that there is a video with this one. You can hear the entire webinar as well as reviewing the slides.

Quantified Self Meetup, Ann Arbor

Cool Toys, Devices, Quantified Self

Last week, I felt really lucky that I was able to make it to the first Quantified Self Meetup of the New Year (thanks to Nancy Gilby for the ride!). This session was held at the UMSI Entrepreneurship Center. Roughly ten folk came, and I’m not sharing names even though they said I could because I’m not sure I got the names down right. The group included a wide range of types of people: corporate folk, students, entrepreneurs, faculty, alumni, and independents. The conversation was fast, dynamic, and overlapping, so I couldn’t catch everything. I will talk about what I did catch of the IDEAS and the GADGETS. That’s what’s really fun, eh?

INTERESTS

What the Meetup group page SAYS they are interested in (as a sampling) is pretty extensive.

“Aging in Place Technology • Behavior change and monitoring • Caregiving of digital patients • Chemical Body Load Counts • Citizen science• Digitizing Body Info • Medical Self-Diagnostics • Lifelogging• Location tracking • Non-invasive Probes• Mindfulness and wisdom tracking • Parenting through monitoring/ tracking • Personal Genome Sequencing • Psychological Self-Assessments • Risks/Legal Rights/Duties • Self Experimentation • Sharing Health Records • Wearable Sensemaking”

What’s even more interesting is what people said they were interested in as they went around the table.

  • aging population
  • big data
  • biohacking
  • data visualization
  • diabetes
  • epigenetics
  • fitness
  • geofencing
  • legal advice
  • patient communities
  • personal genomics
  • sleep tracking
  • telehealth

The “legal advice” bit? That was from someone planning a wearable tech start up. They got some interesting answers on that point: Scott Olson, of UM’s Pediatric Device Consortium; SPARK; Medical Innovation Center, Fast Forward Medical Innovation, and (depending on your UM affiliation) possibly the Student Legal Services, UM’s Startup Law Clinic (Twitter), Zell Lurie Institute.

For the personal genomics, it was a great surprise to me to meet another person who knows their MTHFR status (and who also has two defective copies of the gene, AND is working on problem solving as hard as I am)! We were swapping info, apps, diet tips and tricks, formulations of supplements, and more. There just wasn’t enough time to dig as deeply into this as I wished. I did get to do my now normal rant, “23andMe was NOT killed off!”

ISSUES

After introductions, we just had an open conversation, much of which touched on challenges in quantified self tools. This was what had the meeting stretching WAY past the planned time!

  • QS devices are not being designed for longevity, but for rapid failure
  • QS devices are not being designed to actually work, by and large, which is frustrating to folk buying them early, and an argument for doing QS with low-tech self-hacked solutions
  • to integrate into personal healthcare solutions, there is a need for calibration with official medical devices
  • how are data measurements defined? it. “sleep” cycles based on movement, rather than REM cycles.
  • desperate need for standards of measurement, to empower folk wanting to discover trends and patterns across tools, data sources, and apps
  • who is funding these?
  • data visualization for self-discovery; “correlation” vs aggregator apps; challenges of meaningful analysis
  • HIPAA and QS: patient self-reporting data as an FDA loophole; PHI – Personal Health Information (personal sharing loophole)
  • requirements for insurance coverage – need doctor’s prescription for some very useful medical devices; reimbursement codes can be tricky
  • reverse innovation
  • risk science, risk of failure, costs of failure
  • when designing a device, think about how will it fail?
    design for how to make it work or how to make it fail?
  • how can small companies compete? “innovative/unique, protected, acquired”
  • security, open data, hack into someone else’s data, ownership of data

Any one of these could easily be a devoted session, presentation, or series of blogposts. The bit about failure especially interested me. The idea was that these devices seem to be being designed to fail, as is pretty standard for tech in general these days. But what happens to the end user if they get to the point where they trust the wearable tech device, trust its data, and can’t tell that it has stopped working properly or is on the verge of failure? The FDA keeps tabs on what happens with medical device failures in their MAUDE database. The problem is that this only applies to devices that go through FDA approval, and most of the wearable tech devices folk use for biohacking or self-tracking personal health information, well, they are not FDA approved. People were talking about how much risk is there, impacts, and devices that are low risk. I shared a story of a time when a blood pressure cuff lead to a fatality some decades ago. That was pretty shocking to them, because we tend to think of blood pressure cuffs as being pretty innocuous. How did it happen? It failed during surgery, and kept giving normal readings when the patient was actually having trouble. The idea was that even simple tech can have serious impacts when the stakes are high and people are depending on it.

DEVICES, SERVICES, APPS, & MORE

Of course, we all had to talk about our toys, how we like them or don’t, what we’d change, what we’re thinking about buying, our experiences with customer service from the different companies, companies that are failing or expanding, new releases, etc. I tried to keep a list of devices mentioned or waved around (not all of which were pertinent to QS), but I’m pretty sure I missed a few. The same is true of services, apps, and such, but I’ll give links for the ones I caught.

DEVICES

While most of the gadgets mentioned were in the room and functional, that wasn’t true across the board. Some of these were mentioned as warnings (“a glorified pedometer” “gave me headaches” “out of business”), so please don’t take this list as an endorsement.

SERVICES

I know there was another few genetic analysis tools mentioned that I can’t remember, and I’m really frustrated that I can’t remember. Later, trying to prod my memory, I found this great list (“What else can I do with my DNA test results?“) but I’m still hoping that the person who mentioned the other tools will comment on this post with what I missed.

APPS / SOFTWARE

The apps here include tools for mobile and desktop, for data analysis, self-tracking, behavior modification, communities, and time management / lifehacking. What isn’t included is the conversation about low-tech alternatives, such as replacing calorie counting apps with photos of what you ate, or using notebooks instead of tracking apps. Quantified self doesn’t have to take a lot of money and gadgets (but perhaps that should be a separate post).

RESOURCES

Please note that this is NOT a collection of the best ever anywhere resources on Quantified Self, but rather (as with all the other lists in this post) a collection of what was mentioned during the meeting.

Last but not least, I collected a whole bunch of links I stumbled on during the meeting in one large “OneTab” collection. It includes 76 web pages that I wanted to come back to, reflecting more details or random conversation digressions. You can find it here: http://www.one-tab.com/page/EKdC99v0Q2-nZYfOm41lOw.